calcAUC

 A vector of scores. This could be, e.g. one of the columns of the statistics of a <code><a rd-options="" href="/link/DEResult?package=puma&version=3.12.0" data-mini-rdoc="puma::DEResult">DEResult</a></code> object. 

scores

 A boolean vector indicating which scores are True Positives. 

truthValues

 A vector of indices indicating which scores (and truthValues) are to be used in the calculation. The default is to use all, but a subset can be used if, for example, you only want a subset of the probesets which are not True Positives to be treated as False Positives. 

includedProbesets


	Calculates the AUC values for one or more ROC plots.


manip

Most analyses of Affymetrix GeneChip data (including tranditional 3' arrays and exon arrays and Human Transcriptome Array 2.0) are based on point estimates of expression levels and ignore the uncertainty of such estimates. By propagating uncertainty to downstream analyses we can improve results from microarray analyses. For the first time, the puma package makes a suite of uncertainty propagation methods available to a general audience. In additon to calculte gene expression from Affymetrix 3' arrays, puma also provides methods to process exon arrays and produces gene and isoform expression for alternative splicing study. puma also offers improvements in terms of scope and speed of execution over previously available uncertainty propagation methods. Included are summarisation, differential expression detection, clustering and PCA methods, together with useful plotting functions.

Xuejun Liu

puma

Propagating Uncertainty in Microarray Analysis(including
Affymetrix tranditional 3' arrays and exon arrays and Human
Transcriptome Array 2.0)

calcAUC function

 A vector of scores. This could be, e.g. one of the columns of the statistics of a <code><a rd-options='' href='DEResult'>DEResult</a></code> object. 

calcAUC: Calculate Area Under Curve (AUC) for a standard ROC plot.

Description

Usage

Arguments

Value

See Also

Examples